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In 16 subjects, mismatched codes contributed to a significant difference in structured diagnosis coefficient (ie, >0.35).
When the ICU admission diagnosis was unavailable or not coded by the automatic tool, the corresponding predictive coefficient was replaced by the 'generic' adjusted diagnosis coefficient of −0.42772.
Correlation statistics and Bland Altman plots were used to compute the agreement in coding diagnosis coefficient using different mapping methods, manual, gold standard and automatic.
On plotting the Bland Altman plot using the difference and mean value of the diagnosis coefficient coded manually and by the automatic tool, the bias between methods in coding diagnosis coefficient was found to be 0.168 (95% CI −0.799 to 1.135) (figure 3).
On drawing Bland Altman plot for diagnosis coefficient coded by three methods, bias between gold standard and automatic calculation tool, calculation was intermediate: −0.102 (95% CI −0.881 to 0.677) (figure 1).
In a derivation cohort of 192 consecutive critically ill patients, the diagnosis coefficient coded by three different methods had a positive correlation, highest between manual and gold standard (r=0.95; mean square error (MSE =0.040) and least between manual and automatic tool (r=0.88; MSE=0.066).
Similar(53)
Adjusted diagnosis coefficients were calculated using mean structured diagnosis coefficients, adjusted for diagnosis prevalence.
The structured diagnosis coefficients for these conditions are very similar to each other, −0.55183 and −0.57947, respectively.
All models included 48 dummies for primary diagnosis (coefficients not shown here); ICD: whether patient received an ICD (1) or not (0).
Hence, although incident cases and procedures were under-ascertained, fair to very good agreement between the two data sources was shown for cancer diagnosis (κ-coefficient ranging from 0.42 to 0.84) and curative surgery (κ-coefficient ranging from 0.68 to 0.83) (Table 1).
However, even if we control for the full diagnosis vector, the coefficient is still negative and statistically significant.
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Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com